CMTNet: a hybrid CNN-transformer network for UAV-based hyperspectral crop classification in precision agriculture

Abstract Hyperspectral imaging acquired from unmanned aerial vehicles (UAVs) offers detailed spectral and spatial data that holds transformative potential for precision agriculture applications, such as crop classification, health monitoring, and yield estimation. However, traditional methods strugg...

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書誌詳細

出版年:	Scientific Reports
主要な著者:	Xihong Guo, Quan Feng, Faxu Guo
フォーマット:	論文
言語:	英語
出版事項:	Nature Portfolio 2025-04-01
主題:	Hyperspectral imaging Crop classification Multi-output feature constraints Convolutional neural networks Transformer
オンライン･アクセス:	https://doi.org/10.1038/s41598-025-97052-w